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The Power of Caching: Boosting API Performance and Scalability

DZone

Caching is the process of storing frequently accessed data or resources in a temporary storage location, such as memory or disk, to improve retrieval speed and reduce the need for repetitive processing.

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Cache and Prizes

Alex Russell

Browsers will cache tools popular among vocal, leading-edge developers. There's plenty of space for caching most popular frameworks. The best available proxy data also suggests that shared caches would have a minimal positive effect on performance. Suppose a user has only downloaded part of the cache.

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Top Redis Use Cases by Core Data Structure Types

Scalegrid

Redis , short for Remote Dictionary Server, is a BSD-licensed, open-source in-memory key-value data structure store written in C language by Salvatore Sanfillipo and was first released on May 10, 2009. Depending on how it is configured, Redis can act like a database, a cache or a message broker. Data Structures in Redis.

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Redis vs Memcached in 2024

Scalegrid

In this comparison of Redis vs Memcached, we strip away the complexity, focusing on each in-memory data store’s performance, scalability, and unique features. Redis is better suited for complex data models, and Memcached is better suited for high-throughput, string-based caching scenarios.

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Key Advantages of DBMS for Efficient Data Management

Scalegrid

Enhanced data security, better data integrity, and efficient access to information. This article cuts through the complexity to showcase the tangible benefits of DBMS, equipping you with the knowledge to make informed decisions about your data management strategies. What are the key advantages of DBMS?

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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Effective management of memory stores with policies like LRU/LFU proactive monitoring of the replication process and advanced metrics such as cache hit ratio and persistence indicators are crucial for ensuring data integrity and optimizing Redis’s performance. All these contribute significantly towards ensuring smooth functioning.

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Seamlessly Swapping the API backend of the Netflix Android app

The Netflix TechBlog

This allowed Android engineers to have much more control and observability over how we get our data. Background The Netflix Android app uses the falcor data model and query protocol. For example, the artwork service is separate from the video metadata service, but we need the data from both in the detail key.

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